1. Field of the Invention
The present invention is in the area of digital imaging, and pertains more particularly to apparatus and methods for enhancing and improving digital images, in particular by unskilled consumers.
2. Discussion of the State of the Art
Typically the visual enhancement of digital images is performed using software packages that involve a variety of photo-editing techniques and algorithms. These may involve the user in procedures such as defining the values of a set of control parameters, moving variable sliders, manipulating adjustable-curves, or pressing ‘try-this’ buttons that incorporate specialist algorithms. All these may work to a greater or lesser extent, but by virtue of their user—and/or their computational—complexity, they remain largely the province of the professional or advanced and experienced user, and beyond the technical capabilities of the greater proportion of potential users.
An additional drawback is implicit in the menu-driven approach to most photo-editing and enhancement software tool-sets. In fact both the statistical image-quality attributes, and hence their physical surrogates within the image pixel-parameters, are generally each interconnected to each other, since they are neither independent nor commutable. Thus both the magnitude of the image-manipulation due to the adjustment of a particular parameter, and the order in which it is applied to the digital image, is generally of unspecified hierarchal importance: each adjustment may partially undo the effects of one or more previous adjustments. Therefore, in general only a skilled operator with experience can establish comprehensive image-enhancement recipes minimizing such interacting problems, such recipes typically being based on experimentation with many digital images.
A further complication in many existing image enhancement methodologies arises from an attempt to provide global algorithms, either to embed in the hardware of acquisition devices or to incorporate in user software. The demands made on these algorithms, simultaneously adjusting all or many of the basic image-quality parameters, are such that they typically operate only conditionally on pixels, where these conditions are determined by various collective attributes of defined sets of other local pixels. All such conditional pixel operations themselves inevitably introduce their own image signature to the enhanced image, and this signature often shows in the form of new and undesirable image-quality defects introduced by the algorithms themselves. Some of the more obvious of these defects manifest themselves as image-contouring, haloes, pronounced ‘ringing’ and dark-lines at boundaries of image detail, post-enhancement local color-misbalances, the presence of image-regions of excessive noise, and so on. User attempts to optimize the visual image-quality may thus call for a delicate balancing act between enhancing natural image-quality parameters and the simultaneous introduction of new and unintended but inevitable image defects.
On the other hand, the number of consumer digital images existing for example from digital cameras and cell-phones, photo-scanners and the web, continues to proliferate at a very high, and increasing rate, and a majority of these images could readily be enhanced to the user's benefit and satisfaction, if a truly user-friendly enhancement methodology were readily available, which does not suffer from the drawbacks described above.
While there seems to be considerable content in the art concerning photo-editing techniques and algorithms, covering but not limited to brightness and darkness variations, tone and contrast adjustments, and the balance of the image color-components, and while these techniques and algorithms may involve a host of manipulations on the basic constituents of the digital image (for example, the pixel-histogram, its extent, distribution and other statistics, and the relative color components of the pixels), there is art known to the present inventor concerning a methodology whereby users are presented with a choice of automatically-selected enhancements to their pictures; wherein a first choice may lead naturally to a next best choice, and so on; and where a short series of such choices may lead rapidly to a picture optimized for image quality according to the personal visual preferences and criteria of the user.
One reason for the many difficulties described concerns complexity of components defining image quality and their statistical representation in pixel-array properties, and the very large number of combinations of these components. For each image, with its own peculiarities of scene composition and lighting, digital-acquisition devices must in effect make a technical estimate of the combination of those image-quality properties and combinations most likely to satisfy the user. Likewise, after-the-fact software packages typically make implicit assumptions of these same properties, and then present a system of controls whereby the user may attempt to obtain simultaneous preferential values of all these properties.
A quantitative estimation of the scale of the problem described above can be established as follows. If one considers quite basic image-quality variables of image brightness and darkness, tone and contrast, and contributions made by color components of the image, and if further one devises a linear scale for basic image variables, and within this scale defines increments of user image-quality discrimination, then for any image such an exercise leads to an estimated number of magnitude typically in excess of one-hundred-thousand possibilities for all combinations of these fundamental variations. Thus, just as image-acquisition devices (for example, digital camera or scanner) must in effect attempt a best technical guess at an optimum combination from amongst this very large number, so does any remedial software when the acquisition technology is sub-optimum in any or all of these image aspects. The chance of this guess being best is remote.
An entirely novel approach would be one of presenting the user with each of the very large number of possible images, and letting the user make an individual choice of the optimum preferred image-quality based entirely on personal preference. If this could be done efficiently, the practical need for a menu of enhancement techniques as described above would largely disappear. A practical reason this approach has not previously been pursued is implicit in the above estimation for the large number of practically distinguishable image choices (that is, typically in excess one-hundred thousand). Note that calculation of this number itself involves definition and separation, linear-visual-scaling, interval-determination and combinatory calculation of basic image variables. This exercise presents a formidable task in itself, and has no known coverage in the prior art for practical digital images, to the knowledge of the present inventor. One approach in an aspect of the present invention includes methodology for practical determination of a number of individual image combinations, or a number of possible image quality states for any single original digital image.
Having established a number of independent image quality states, the problem of presenting these states for user-selection seems at first consideration to be formidable. For example, automatically printing in excess of, say, one-hundred-thousand prints representing each state, and letting the user make a choice, would be clearly prohibitive in time and cost, while displaying them in electronic form, for example on a computer monitor, would seem not only to be costly in time but tedious and confusing to the user.
What is clearly needed is a simple, practical digital-image enhancement procedure, yet one that overcomes the existing problems and complications associated with conventional software systems, while at the same time removing obvious barriers to practical application.